Principal Data Scientist
BayOne Solutions
- Advanced experience designing, building, and deploying machine learning solutions in production environments at enterprise scale.
- Strong expertise in Python and modern machine learning frameworks such as Scikit-Learn, TensorFlow, PyTorch, XGBoost, or similar technologies.
- Deep experience developing machine learning models including:
- Random Forest
- Isolation Forest
- Classification Models
- Regression Models
- Clustering Algorithms
- Anomaly Detection Frameworks
- Predictive Analytics and Forecasting Models
- Proven track record operationalizing AI/ML solutions from experimentation through production deployment and monitoring.
- Strong understanding of feature engineering, model evaluation, model explainability, and MLOps best practices.
- Experience building scalable ML pipelines and workflows using orchestration frameworks such as Airflow, Kubeflow, MLFlow, or similar platforms.
- Strong data engineering foundations including SQL, data modeling, ETL/ELT design, and distributed data processing.
- Experience working with BigQuery, Spark, DBT, Databricks, or comparable cloud-scale analytical platforms.
- Experience with cloud-native architectures and services across Azure, Google Cloud Platform (GCP), AWS, or hybrid cloud environments.
- Hands-on experience developing and deploying microservices, REST APIs, containerized applications, and Kubernetes-based solutions.
- Experience with CI/CD practices and software engineering principles for scalable AI platform development.
- Strong knowledge of NLP, semantic search, vector embeddings, Retrieval-Augmented Generation (RAG), LLMs, and Generative AI applications.
- Experience building intelligent systems leveraging embeddings, vector databases, and modern AI agent frameworks is highly preferred.
- Demonstrated ability to lead technical strategy while influencing cross-functional stakeholders across engineering, product, analytics, and business organizations.
- Exceptional problem-solving, analytical thinking, and communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences.
- Proven ability to mentor teams, establish technical standards, and drive adoption of AI/ML best practices across large organizations.
- Passion for innovation and building the future of intelligent audit, analytics, and decision-support platforms.
Vacancy posted 4 days ago
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